An acoustic Wireless Sensor Network for remote monitoring of bird calls
2016 IEEE International Conference on Information and Automation for Sustainability (ICIAfS)(2016)
摘要
Wireless Sensor Network (WSN) based acoustic monitoring is useful for ecologists for the purpose of monitoring real-time wildlife behavior across remotely located large areas, for long periods and under variable weather/climate conditions. However, stringent requirements for intense data processing and data bandwidth across network nodes makes applicability of WSN based monitoring limited. This paper presents, a mesh network of wireless sensor nodes that only requires readily available hardware, algorithms and methods for acoustic source type identification. A node was constructed by interfacing three separate modules to a microprocessor: (i) a microphone coupled to a USB sound card for recording acoustic data, (ii) a radio frequency (RF) transceiver for inter-node and remote server communication, and (iii) an external Real Time Clock module for time-synchronization between nodes. The system was designed for real-time identification of calls of Black-Rumped Flameback (BRF), a type of woodpecker endemic to the Indian sub-continent and found in parts of Sri Lanka. Any acoustic signal above a predefined intensity threshold was recorded while BRF calls were discriminated with respect to two other known bird calls. This was achieved based on a threshold estimated by measuring the cross-correlation between two known BRF calls. This method was able to successfully identify 83% of the tested BRF calls. Several more frequency domain features were also identified that are compatible with Support Vector Machines (SVM), which is a more robust identification algorithm. The SVM based was able to successfully identify 91% of the tested BRF calls. The total cost of hardware used per node was estimated to be under USD 75.
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关键词
WSN,Black-Rumped Flameback,SVM
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